code: def test_split_results(self):
      pred_results = [
          dict(
              cls_res=torch.rand(2, 4, 10, 10),
              reg_res=torch.rand(2, 21, 10, 10),
          ),
          dict(
              cls_res=torch.rand(2, 4, 20, 20),
              reg_res=torch.rand(2, 21, 20, 20),
          ),
          dict(
              cls_res=torch.rand(2, 4, 40, 40),
              reg_res=torch.rand(2, 21, 40, 40),
          ),
      ]
      postprocessor = FCEPostprocessor(
          fourier_degree=5, num_reconstr_points=20, score_thr=0.3
      )
      split_results = postprocessor.split_results(pred_results)
      self.assertEqual(len(split_results), 2)
      self.assertEqual(len(split_results[0]), 3)
      self.assertEqual(len(split_results[1]), 3)
      self.assertEqual(
          split_results[0][0]["cls_res"].shape, (4, 10, 10)
      )
      self.assertEqual(
          split_results[0][0]["reg_res"].shape, (21, 10, 10)
      )
  
file_path: mmocr/tests/test_models/test_textdet/test_postprocessors/test_fce_postprocessor.py
imports: import unittest
  import numpy
  import torch
  from mmengine.structures import InstanceData
  from parameterized import parameterized
  from mmocr.models.textdet.postprocessors import FCEPostprocessor
  from mmocr.structures import TextDetDataSample
label_desc: Use image node_id 1 for calling the TestFCEPostProcessor obj's underlying member method code with example usage: obj.test_split_results() without return types